Built AI-assisted maintenance prototype now quoted to major industrial customer

Achievements

- Built a working prototype of an AI-assisted maintenance workflow for industrial equipment inspections. (Only pump inspections shown on this project.)

- Centralized inspection documentation, approvals, and scheduling into one structured system.

- Implemented automated approval triggers and email notifications to simulate supervisor review.

- Demonstrated how defined operating thresholds (pressure, temperature) can trigger intelligent recommendations.

- Developed a 10-year roadmap for three digital maintenance employees (IMA, ITA, IDA).

·       Currently in active discussions with a major industrial customer and have submitted a formal quote for deployment of the first two digital employees (IMA and ITA).

Tools

- Airtable (relational database, interfaces, forms)

- Airtable Automations (email notifications)

·       Formula fields and conditional logic for threshold flagging

Methodology

- Identified industry need: aging maintenance workforce and loss of institutional knowledge.

- Designed structured inspection forms with defined operational parameters.

- Built relational links between Parts, Inspections, Approvals, and People.

·       Simulated supervisory approval workflow through automation.

Learnings

- Structured data architecture is foundational before deploying advanced AI agents.

- Even lightweight automation significantly improves maintenance visibility.

·       Clear operational limits enable meaningful AI-assisted decision support.

Relevant URLs

- Read-only Airtable Base Link: https://airtable.com/invite/l?inviteId=invYr16veu7I9O0WL&inviteToken=537e9ca18f157876e29c779ca4a9aa9822790392f0aed2da57e32e2f1cbe605c&utm_medium=email&utm_source=product_team&utm_content=transactional-alerts

- Pump Inspection Form Link: https://airtable.com/appENhCD66IuTVQSL/pagRopsZ007jv73J1/form

New Parts Form: https://airtable.com/appENhCD66IuTVQSL/pagYCqCUSDGCb8zXf/form